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Multiplex Interbank Networks and Systemic Importance: an Application to European Data

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Multiplex Interbank Networks and Systemic Importance: an Application to European Data Working Paper Series Iñaki Aldasoro, Iván Alves Multiplex interbank networks and systemic importance: an application to European data No 1962 / September 2016 Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. Abstract Research on interbank networks and systemic importance is starting to recognise that the web of exposures linking banks balance sheets is more complex than the single-layer-of-exposure approach. We use data on exposures between large European banks broken down by both maturity and instrument type to characterise the main features of the multiplex structure of the network of large European banks. This multiplex network presents positive correlated multiplexity and a high similarity between layers, stemming both from standard similarity analyses as well as a core-periphery analyses of the different layers. We propose measures of systemic importance that fit the case in which banks are connected through an arbitrary number of layers (be it by instrument, maturity or a combination of both). Such measures allow for a decomposition of the global systemic importance index for any bank into the contributions of each of the sub-networks, providing a useful tool for banking regulators and supervisors in identifying tailored policy instruments. We use the dataset of exposures between large European banks to illustrate that both the methodology and the specific level of network aggregation matter in the determination of interconnectedness and thus in the policy making process. Keywords: interbank networks, systemic importance, multiplex networks JEL Classification: G21, D85, C67. ECB Working Paper 1962, September 2016 1 Non-technical summary The recent financial crisis and the stress suffered in interbank markets brought to the fore the relevance of interconnectedness between banks and the importance of higher-order feedback loops embedded in the reciprocal web of exposures linking financial institutions. Network theory and network-based analytics have proven useful in extracting relevant information from systems that due to their inherent complexity do not lend themselves to simple apprehension. Of critical importance in macro prudential policy is the identification of key players in the financial network. In the context of interconnectivity analysis, the identification of critical nodes within a network has been a problem long studied in disciplines like sociology, under the heading of ”centrality” analysis. While early contributions on interbank contagion and networks have focused on aggregated exposures, it is now increasingly recognised that the web of credit relationships linking banks’ balance sheets is in general more intricate and complex. Macro prudential policy addressing banks’ systemic importance could indeed benefit from the consideration of subnetworks and aggregated network separately: systemic importance may depend on which activity is at the time more critical or the target of a specific policy. The paper presents a unique dataset of exposures between large European banks that features a high level of disaggregation in terms of instruments and maturity. We analyse its multiplex structure by means of correlated multiplexity, core-periphery and similarity analyses. Additionally, we introduce two new accounting-based measures designed for multiplex (or mul- tilayer) networks, which build a systemic importance score for each bank in the aggregated network that can be decomposed into the contributions by each sub-network. This provides a holistic analy- sis that truly incorporates the multiplex structure of the network, instead of doing separate analyses for the different layers and the aggregate network. We use the dataset of exposures between large European to illustrate the measures. Our approach builds on the logic that drives the policy pro- cess of assessing banks’ importance at the Financial Stability Board (FSB) in its recognition of the importance of interconnectedness, but delves deeper into this aspect by considering the different layers in an integrated accounting framework. The insights from the measures proposed can be of policy relevance for supervisors and regulators. ECB Working Paper 1962, September 2016 2 1 Introduction Growing interest in the analysis of financial interconnectedness and the assessment of systemic risk reflect policy interest extending well beyond traditional micro-prudential supervision. Risk externalities of bank behaviour, which are not taken into account by micro-prudential policies, call for a macroprudential approach. The recent financial crisis and the stress suffered in interbank markets brought to the fore the relevance of bank interconnectedness and the importance of higher- order feedback loops embedded in the reciprocal web of exposures linking financial institutions. Of critical importance in macroprudential policy is the identification of key players in the fi- nancial network, as exemplified by recently introduced Basel Committee on Banking Supervision (BCBS) requirements on globally systemic important banks (G-SIBs). In the context of network interconnectivity analysis, the use of “centrality” indicators attempt to assess, based on different criteria, how important a node is for the functioning of the network under study. While early contributions on interbank contagion and networks have focused on aggregated exposures, it is now increasingly recognised that the web of credit relationships linking banks’ balance sheets is in general more intricate and complex. The empirical literature thus far has either disregarded heterogeneity in credit relationships or worked with only one layer (typically the overnight unsecured market) resting on the tenet that it is representative of the whole web of exposures.1 Of course, there is a very good reason why most of the extant literature on interbank networks has worked with the simplification of a single layer of exposures, namely data availability. Macro prudential policy addressing banks’ systemic importance could indeed benefit from the consideration of subnetworks and aggregated network separately. To the extent that transmission channels’ magnitude and speed differ across layers, institutions’ systemic importance may differ at the aggregate and more granular levels. Furthermore, systemic importance may depend on which activity is at the time more critical or more directly addressed by the specific policy being considered. This is not hard to understand given the derivation of systemic importance: a given bank’s aggregated systemic importance could be seen as being composed of importance in the different subnetworks, thus possibly accounting for the multiple feedback loops that can exist when banks are connected at different levels or layers of exposure. This is indeed the logic that drives the policy process of assessing banks’ importance at the Financial Stability Board (FSB) and the Basel Committee on Banking Supervision, whereby global importance is constructed by an aggregation of the size of the banks in relevant activities (see Basel Committee on Banking Supervision (2013)). Distinguishing aggregate from granular components of systemic importance is an improvement over, for example, past practice of considering only banks’ size. Explicitly addressing banks’ importance and complexities associated with interconnections within a financial system through activities not recognised by the size of their balance sheets is key for financial stability assessment. Thus, the 1Exceptions to this are the recent contributions by Bargigli et al. (2015) and Langfield et al. (2014) among others. See the literature review section below for more details. ECB Working Paper 1962, September 2016 3 regulatory definition of systemically important banks adopted by the BCBS and the FSB rests on distinctly recognising all the bank activities central to the financial system and (exogenously) weighing them to derive a unique ranking of systemic importance.2 This recognition dates back to the ECB’s surveillance of large and complex banking groups, which acknowledged the usefulness of refining the degree of centrality of banks in such a way that banks’ importance relative to a given fragility can be identified. In an environment of scant or rapidly changing liquidity, for instance, it is central to policy makers’ interest to identify banks important in the provision of short term loans. Likewise, the more structural provision of long term financing among banks is best understood in light of banks’ importance vis-`a-vislonger term funding. The policy interest may centre on a bank’s importance relative to the activity of a given market, and the picture provided by an aggregate interconnectivity analysis that does not allow for a decomposition may be misleading. Without granular information allowing to observe a bank’s centrality in the interconnectivity of these activities, the scope of policy action remains limited. The papers addressing different layers of exposures between banks typically perform separate analyses for each layer and the aggregated network.3 Our paper contributes to this literature by building on a holistic representation of the balance sheet of the banking system that allows for a consistent decomposition of systemic importance. To this end, in the present paper we build on the framework introduced by Aldasoro and Angeloni (2015) and expand two of their systemic importance measures to the case in which banks
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